Project Abstract

Spam emails are a major issue in today?��s culture as they have a significant impact on emailcommunication and online advertising. People are using spam emails for illegal, malicious,and unethical contacts with the intent to harm our system or scam us. To that effect, over theyears, IT specialists are continuously trying to identify the spams and create various antidoteprogrammes to effectively tackle and eliminate these kinds of emails.In this project, I have applied machine learning algorithm and homomorphic encryption in aneffort to develop a reliable system that identifies and eliminates the problem. Spamidentification using Machine learning and homomorphic encryption enables the developmentof a secure and reliable system to detect and filter spam. Machine learning is a usefultechnique used for recognizing and minimizing Spam. Equally, a machine learning model is acomplex algorithm that processes sensitive data with the purpose of finding patterns andmaking predictions. Conversely, this raises many questions about privacy and security whichI will try to mitigate and resolve.Furthermore, in this project I used partial homomorphic encryption with the PaillierEncryption Scheme, which is a probabilistic asymmetric algorithm for public keycryptography, enabling computations to be performed on encrypted data, without requiring itto be decrypted first.By using Spam Identification with Machine Learning and Homomorphic Encryption weenabled the user to train a machine learning model with encrypted data, thus protecting theprivacy of the data that are being used. Hence in this project, I have adopted a new approachto address the serious problem of SPAM identification, offering an alternative solution to theexisting complex, heavy-weighted and non-secure existing methods.

Keywords: Machine Learning, Homomoprhic Encryption, Paillier Encryption

 Conference Details

Session: Poster Session A at Poster Stand 26

Location: Sir Stanley Clarke Auditorium at Tuesday 7th 13:30 – 17:00

Markers: Hans Ren, Amjad Amjad

Course: BSc Computer Science, 3rd Year

Future Plans: I’m looking for work